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We demonstrate the power and utility of the proposed workflow using multiple examples.
The proposed workflow consists of three components: history matching, model selection and production optimization.
The uncertainties related to the main parameters that affect the volumetric calculation were incorporated into the proposed workflow.
This paper presents the results of experiments done in different stages of the proposed workflow.
As a first step the proposed workflow sets the relevant planning goals and assesses the protection structure functionality.
The proposed workflow benefits from the combination of finite element submodeling techniques and modal superposition method with the new concept of modal stress intensity factors.
The results demonstrate the effectiveness of the proposed workflow as well as the feasibility and high efficiency of airborne LiDAR for highway inventory data collection.
Introducing this workflow, and how the proposed workflow reduces the volume of post-optimization paneling waste by 2% at its minimum are the major findings here.
Results highlight the relevance of the proposed workflow for informing decisions about early-stage building massing on the basis of the considered performance criteria.
With the provided flexibility of the proposed workflow, it is possible to incorporate various parameters including injection flow rate, temperature, and location.
The proposed workflow has been integrated into the Knowledge Discovery in Databases (KD3) Designer tool, our self-designed and cost-free software package.
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